Change Detection in Animated Choropleth Maps

Master’s thesis, Michigan State University, 2010

Carolyn Fish

“Computer animation enables cartographers to visualize time-series data as never before; we can build dynamic map sequences that congruently depict change over time. However, map readers have difficulty comprehending these animations, and they often fail to detect important changes between adjacent scenes, this is called change blindness. These potentially overwhelming perceptual burdens, such as change blindness, threaten the effectiveness of animated maps in which several important changes can occur simultaneously throughout the display. Animated maps also require viewers not only to notice changes but also understand the transitions within these dynamic displays. Graphic interpolation between display frames, also known as “in-betweening” or “tweening”, smoothes transitions and lengthens the duration of the transition between scenes in an animated map series. Previous cartographic literature suggests tweening as one potential solution for change blindness in animated cartography. This thesis tested the influence of change blindness on animated choropleth map reading and evaluated the influence of tweening to increase change detection abilities of map readers. Empirical results from this research indicate that map readers, 1) have difficulty detecting changes in these types of maps, 2) often fail to comprehend these maps fully, and 3) are influenced by the use of tweening between the scenes of the animated map.”

Small-Scale Unmanned Aerial Vehicles in Environmental Remote Sensing: Challenges and Opportunities

GIScience & Remote Sensing, Volume 48, Number 1 / January-March 2011

Perry J. Hardin and Ryan R. Jensen

“Although potential applications abound, small-scale unmanned aerial vehicles have not yet been widely used for environmental remote sensing. Several challenges remain to be overcome until widespread adoption is possible. One problem is the challenge inherent in flying fragile small-scale aircraft with low weight limits and narrow center of gravity tolerances. Other challenges include: (1) the hostile natural environment in which the aircraft fly; (2) the limits of on-board power; (3) the paucity of commercially available sensors; (4) the difficulties involved in managing and analyzing the large imagery volume generated during a sortie; and (5) the federal regulations in the United States designed to ensure the safety of commercial and private air travel. Each of these challenges is formidable, and overcoming them will require the use of technologies that are currently experimental. However, within each challenge are opportunities for researchers willing to act as innovative pioneers in the remote sensing community.”

Using Geospatial Data and Principles of Landscape Ecology to Identify Field Sites and Characterize Landscapes

Annals of GIS, Volume 17, Issue 1, 01 March 2011

Michael C. Parrish; Jeffrey Hepinstall-Cymerman

“We explored the utility of using readily available geospatial datasets to assist in field site identification. Specifically, we used readily available geospatial data to locate potential field sites that represented specific points along an urban-rural gradient of development intensity at landscape and regional scales. We also incorporated development age (young versus mature) in our site selection. Using publicly available spatial datasets, we computed a set of variables that characterized the landscape at two spatial scales and combined these to develop a gradient of urbanization. We then used maps of these gradients, digital orthophotographs, and ancillary geospatial data layers to identify candidate field sites of the requisite landscape- and regional-scale development intensity. These field sites were then visited to verify the current condition, and acceptable sites were used in companion studies to survey avian communities. We were also interested in how land cover estimates derived from different data sources varied. We compared estimates of percent land cover at two spatial scales derived from coarse scale land cover maps and fine scale screen-digitized from aerial photographs. At finer spatial scales, it appears the added costs associated with screen-digitizing yield much more precise estimates of land cover, whereas at coarser scales, although satellite-based land cover classifications may be somewhat less accurate, they may be sufficiently correlated with aerial photo-interpreted classifications that the expenditure is not worthwhile.”